code: def __iter__(self):
      if self.shuffle_buffer_length is None:
          return iter(self.transformed_dataset)
      else:
          shuffled = PseudoShuffled(
              self.transformed_dataset,
              shuffle_buffer_length=self.shuffle_buffer_length,
          )
          return iter(shuffled)
  
file_path: gluonts/src/gluonts/nursery/robust-mts-attack/pts/dataset/loader.py
imports: from typing import Optional
  import itertools
  from torch.utils.data import IterableDataset
  from gluonts.dataset.common import Dataset
  from gluonts.transform import Transformation, TransformedDataset
  from gluonts.itertools import Cyclic, PseudoShuffled, Cached
label_desc: Use image node_id 2 for calling the TransformedIterableDataset obj's underlying member method code with example usage: obj.__iter__() and returns: iter, iter